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Blind Phase Calibration in Sparse Recovery

Abstract : We consider a {\em blind} calibration problem in a compressed sensing measurement system in which each sensor introduces an unknown phase shift to be determined. We show that this problem can be approached similarly to the problem of phase retrieval from quadratic measurements. Furthermore, when dealing with measurements generated from multiple unknown (but sparse) signals, we extend the approach for phase retrieval to solve the calibration problem in order to recover the signals jointly along with the phase shift parameters. Additionally, we propose an alternative optimization method with less computation complexity and memory requirements. The proposed methods are shown to have significantly better recovery performance than individual recovery of the input signals when the number of input signals are sufficiently large.
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Submitted on : Monday, April 15, 2013 - 3:33:29 PM
Last modification on : Sunday, June 26, 2022 - 2:18:39 AM
Long-term archiving on: : Tuesday, July 16, 2013 - 4:08:03 AM


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  • HAL Id : hal-00813421, version 1


Cagdas Bilen, Gilles Puy, Rémi Gribonval, Laurent Daudet. Blind Phase Calibration in Sparse Recovery. EUSIPCO - 21st European Signal Processing Conference - 2013, Sep 2013, Marrakech, Morocco. ⟨hal-00813421⟩



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